• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1992년도 한국자동제어학술회의논문집(국내학술편); KOEX, Seoul; 19-21 Oct. 1992
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• pp.502-506
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• 1992

In this study, we proposed the fuzzy modeling method and designed a model-based logic controller for Activated and Sludge Process(A.S.P.) in sewage treatment. The identification of the structure of fuzzy implications is carreid out by use of fuzzy c-means clustering algorithm. And to identify the parameters of fuzzy implications, we used the complex and the least square method. To tune the premise parameters automatically the complex method is implemented. The model-based fuzzy controller is designed by rules generated from the identified A.S.P. fuzzy model. The feasibility of the proposed approach is evaluated through the identification of the fuzzy model to describe an input-output relation of the A.S.P.. The performance of identified model-based fuzzy controller is evaluated through the computer simulations.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제3권1호
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• pp.78-86
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• 2003

Multivariable control system exist widely in many types of systems such as chemical processes, biomedical processes, and the main steam temperature control system of the thermal power plant. Up to the present time, Pill Controllers have been used to operate these systems. However, it is very difficult to achieve an optimal PID gain with no experience, because of the interaction between loops and gain of the Pill controller has to be manually tuned by trial and error. This paper suggests a tuning method of the Pill Controller for the multivariable power plant using an immune algorithm, through computer simulation. Tuning results by immune algorithms based neural network are compared with the results of genetic algorithm.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2005년도 ICCAS
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• pp.1264-1267
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• 2005

Fuzzy logic control has been widely applied for handling the system which has uncertainty or high robust system. Since the dynamic behaviors of the systems contain complexity and uncertainty in its parameters, several fuzzy logic controllers have been implemented to control room temperature in the field of air conditioning system. In this paper, the fuzzy logic control has been developed to control both in door temperature and humidity in the air conditioning systems. The manipulating variables are speed of compressor, heater and supply air flow rate. The microcomputer was used to interface with in system. The experimental results show the superior of multivaiable fuzzy logic control to keep room temperature and humidity in air conditioning system for the best comfortable.

• 전자공학회논문지B
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• 제28B권7호
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• pp.557-565
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• 1991

The activated sludge process is a commonly used method for terating sewage and waste waters. The process is chatacterized by a lack of measurement instrumentations and control goals that are not always clear and not well understood. In such process, fuzzy control concept may be able to be adapted, do this paper presents a design method for fuzzy controller based on a selected sub-rule set from the total rule set and a multivariable fuzzy reasoning algorithms. In order to achievesystematic and efficient control of the activated sludge process under a great deal of disiutbances and a variety of perfotmance characteristics, a top-level rule-based fuzzy controller os proposed which provises lower-controllers with the suitable set-points according tothe onput-output states of the process.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1991년도 한국자동제어학술회의논문집(국내학술편); KOEX, Seoul; 22-24 Oct. 1991
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• pp.669-675
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• 1991

Based on process analysis as well as extensive operation experience, two fuzzy expert control algorithms, for startup and control, are proposed for a supercritical fluid extraction process which has high interacting multivariable structure. In the proposed algorithms, a new simple defuzzification method which only requires four fundamental arithmetic rules is also presented. Through numerical simulations, control performance using the proposed control algorithm is compared with that of a different fuzzy algorithm by an other researcher and that of conventional PID-type controllers which are tuned by well-known optimal criteria. Also, the proposed control algorithm has been tested to the bench scale supercritical fluid extraction process. As a consequence, the proposed fuzzy expert controller has shown fast and robust control performance while the other controllers show sluggish and/or highly oscillatory responses.

• 한국지능시스템학회논문지
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• 제5권1호
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• pp.33-42
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• 1995

A practical application of a fuzzy-neuro controller is described for an air-conditioning system. Air-handing units are being widely used for improving the performance of central air-conditioning systems. The fuzzy-neuro control system has two controlled variables, temperature and humidity and three control elements, cooling, heating, and humidification. In order to achieve high efficiency and economical contorl, especially in large offices and industrial buildings, two controllable parameters, temperature and humidity, must be adequately controlled by the three final controlling elements. In this paper a fuzzy-neuro control system is described for controlling air-conditioning systems efficiently and economically. Simulation results confirmed that the fuzzy neuro control system is effective for this multivariable system.

• Journal of Electrical Engineering and information Science
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• 제2권4호
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• pp.28-36
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• 1997

In this paper, robust stability analysis for the fuzzy feedback linearization regulator is presented. Well-known Takagi-Sugeno fuzzy model is used as the MISO nonlinear plant model. Uncertainty and disturbance are assumed to be included in the model structure with known bounds. For these structured uncertainty and disturbances, robust stability of the close system is analyzed in both input-output sense and Lyapunov sense. The robust stability conditions are proposed by using multivariable circle criterion and the relationship between input-output stability and Lyapunov stability. The proposed stability analysis is illustrated by a simple example.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 1995년도 추계학술대회 학술발표 논문집
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• pp.25-28
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• 1995

A Practical application of self-tuning fuzzy controller to a multi-input multi-output complex system of a vehicle engine is investigated. The ovjective is to design a controller to improve the transient performance in torque and RPM mode changes. For the performance improvement in the multivariable comples system, the self-tuning function of internal parameters is essential and practical. The measured output variables using different control schemes are compared the advanteges of the self-tuning fuzzy logic controller are better output performances and the effectiveness in the controller design using many parameters.

• 한국정보통신학회논문지
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• 제16권5호
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• pp.973-981
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• 2012

본 논문에서는 비선형 시스템에 대하여 Takagi-sugeno(T-S) 퍼지 Identification을 이용하여 유도전동기의 비선형 다변수 시스템을 선형화 할 수 있는 새로운 방법을 제안한다. T-S 퍼지 모델의 선형화는 퍼지 규칙들 및 소속 함수들의 산술적인 계산으로 인해 선형화가 쉽지 않다. 그러므로 T-S 퍼지 Identification을 이용하여 퍼지 규칙 및 소속함수들의 추정을 통해 높은 정확도를 가지는 선형 모델로 제공한다.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1998년도 하계학술대회 논문집 B
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• pp.407-409
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• 1998

In order to improve the tracking performance of $2{\times}2$ multivariable control systems, a fuzzy control algorithm with feedforward compensator is represented. The method consists in two steps. First, neglecting interconnections. one designs a fuzzy controller to each individual loop. In the second stage, low-order transfer functions of outputs to reference inputs are estimated. We propose a design method of the feed forward compensator based on the transfer functions. An illustrative example are shown.